Reviews: Incorporating Context into Language Encoding Models for fMRI

This paper compares the embedding of a 3-layer LSTM to the neural responses of people listening to podcasts recorded via fMRI. The experiments vary the number of layers in the LSTM, and then context available to the LSTM and compare it to a context-free word embedding model. This is a strong paper, well written and clear. The results are thorough and there are a few interesting surprises. I have a few questions of clarification. 1) How do the authors account for the differences in number of words per TR due to differing word length and prosody?